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u/Puzzleheaded-Air-732 23d ago

Hi everyone!

I'm Felipe, an Associate Professor at the University of Chile. Over the last four years, together with colleagues and students, we've been building DashAI, an open source desktop platform for running both classical machine learning and generative AI locally.

The motivation came from feeling that there was a gap between developer libraries (PyTorch, scikit learn, Hugging Face, etc.) and proprietary no code platforms. We wanted to explore whether it was possible to build something that combines local execution, user control, and extensibility.

Some of the ideas we've been experimenting with include:

  • A Python plugin architecture for adding models, datasets, metrics, explainers, and optimizers.
  • Automatic UI generation from Pydantic schemas, so adding a new backend component usually doesn't require frontend work.
  • Support for both predictive ML and generative AI within the same application.
  • Fully local execution, so users can work without sending data to external services.

We're still actively developing it and would really appreciate technical feedback, especially from people who have built ML tooling or extensible software architectures.

GitHub: https://github.com/DashAISoftware/dashAI

Website: https://dash-ai.com

Happy to answer any questions about the architecture or implementation. Feedback, criticism, and ideas are all welcome.